Mobile robot, method of navigating the same, and storage medium

ABSTRACT

A mobile robot including a motion actuator; at least one detection sensor configured to detect field information in a movement field of the mobile robot; a guidance generation unit configured to generate a motion guidance policy to a target position from a current position, the motion guidance policy being updated by the guidance generation unit when the field information has been received from the at least one detection sensor; a safety sensitization unit configured to generate a safety sensitized policy which is the motion guidance policy with a reduced velocity magnitude relative to an angle between the motion guidance policy and the current motion of the mobile robot; and a motion actuation unit configured to determine an actuation signal for instructing the motion actuator to project the current motion of the mobile robot in conformity with the safety sensitized policy provided by the safety sensitization unit.

BACKGROUND Field of Disclosure

The present disclosure relates generally to a mobile robotics platformfor navigating a known or unknown topography in an obstacle-avoidingand/or communication-aware manner, a method of navigation for a mobilerobotics platform, and a non-transitory computer-readable storage mediumstoring instructions for causing a computer to navigate a roboticsplatform.

Description of the Related Art

Recently, there has been a growing demand for the development ofrobotics aids, for example, to help first responders in firsthandevaluation of emergency-related incidents. The information obtained bysuch systems is critical and serves as the primary link in a chain ofinformation exchange that leads to making important decisions. To beuseful, it is necessary that such aids provide a human operator withsituational awareness in a timely and constrained manner.

In addition, there are other strict and challenging properties thesetypes of robots should have. In a first responder situation, forexample, a mobile robot should be able to move to a designated area inan unstructured and unknown environment. Robot deployment cannot alwaysrely on accurate maps since they are often not available. The robotshould be able to function under zero a priori knowledge withoutengaging in time-consuming activities reserved for exploration andmapping only. The entire robot's effort should be dedicated to reachingthe target zone of interest using the necessary and sufficientinformation its sensors pick-up en route to the target.

The robot should also be able to accommodate any available a prioriinformation in its database. This information is used to accelerateconvergence and enhance performance. What makes the problem excessivelydifficult in a first responder situation is the requirement that therobot maintains a good wireless communication link with a base station,preferably all of the time. Accommodating hard spatial components (e.g.obstacles) of the environment in an autonomous navigation process may bereasonably understood in terms of spatial geometry and topology.However, accommodating signal strength (the soft component of theenvironment) is still a major challenge. This is due to the fact thatthe spatial distribution of signal strength (FIG. 1) in a clutteredenvironment cannot be described using geometry or topology. Thecomplexity of the situation rapidly increases when soft and hard contextare jointly factored into the projection of a first responder-grademotion for the robot.

U.S. Pat. No. 9,623,564 (incorporated herein by reference in itsentirety) describes using harmonic potential for steering a roboticsplatform from an initial point to a final one in an unknown environment.However, the method can only deal with physical obstacles. It is notequipped to incorporate signal strength in the motion generationprocess.

A synchronization procedure has been partially disclosed (see Ahmad A.Masoud, “A Harmonic Potential Approach for Simultaneous Planning andControl of a Generic UAV Platform”, From the issue “Special Volume onUnmanned Aircraft Systems” of Journal of Intelligent & Robotic Systems:Volume 65, Issue 1 (2012), Page 153-173, incorporated herein byreference in its entirety). However, the procedure in the paper does notguarantee success when guidance is evolving under the influence ofonboard sensory feedback.

Accordingly, it is one object of the present disclosure to provide amobile robot, robotics communication system and/or robotic controlmethod that includes a safety sensitizing stage thereby accommodating orpermitting the capability to convert guidance correctly into anactuating signal and to avoid unintended contact with an obstacle orcommunication dead-zone detected while en route to a designated targetposition.

The foregoing “Background” description is for the purpose of generallypresenting the context of the disclosure. Work of the inventors, to theextent it is described in this background section, as well as aspects ofthe description which may not otherwise qualify as prior art at the timeof filing, are neither expressly or impliedly admitted as prior artagainst the present invention.

SUMMARY OF THE INVENTION

A first aspect of the present disclosure provides a mobile robotincluding: a motion actuator; at least one detection sensor configuredto detect field information in a movement field of the mobile robot; aguidance generation unit configured to generate a motion guidance policyto a target position from a current position, the motion guidance policybeing updated by the guidance generation unit when the field informationhas been received from the at least one detection sensor; a safetysensitization unit configured to generate a safety sensitized policywhich is the motion guidance policy with a reduced velocity magnituderelative to an angle between the motion guidance policy and the currentmotion of the mobile robot; and a motion actuation unit configured todetermine an actuation signal for instructing the motion actuator toproject the current motion of the mobile robot in conformity with thesafety sensitized policy provided by the safety sensitization unit.

A second aspect of the present disclosure provides a method ofnavigating a mobile robot, including the steps of: detecting fieldinformation in a movement field of the mobile robot; generating amovement guidance policy to a target position from a current position;updating, when field information is detected in the detecting step, themotion guidance policy based on the detected field information;generating a safety sensitized policy by reducing the velocity magnitudeof the movement guidance policy relative to an angle between the motionguidance policy and a current motion of the mobile robot; generating anactuation signal for actuating the motion of the mobile robot inconformity with the safety sensitized policy; and driving the mobilerobot by way of the actuation signal.

A third aspect of the present disclosure provides a non-transitorycomputer-readable storage medium storing instructions to cause acomputer to perform the steps of: detecting field information in amovement field of a mobile robot; generating a movement guidance policyto a target position from a current position; updating, when fieldinformation is detected in the detecting step, the motion guidancepolicy based on the detected field information; generating a safetysensitized policy by reducing the velocity magnitude of the movementguidance policy relative to an angle between the motion guidance policyand a current motion of the mobile robot; generating an actuation signalfor actuating the motion of the mobile robot in conformity with thesafety sensitized policy; and driving the mobile robot by way of theactuation signal.

The above aspects provide a mobile robot, a method of navigating amobile robot, and a storage medium which allow for improved navigationand safety of travel in a mobile robotics platform. Another feature ofthe above aspects is the ability to maintain a good wireless signalstrength profile along the trajectory to the target while maintainingsubstantially continuous movement. This enables the mobile roboticsplatform to send and receive data to and from a remote operator most ifnot all the time.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete appreciation of the invention and many of the attendantadvantages thereof will be readily obtained as the same becomes betterunderstood by reference to the following detailed description whenconsidered in connection with the accompanying drawings, wherein:

FIG. 1 illustrates a topography containing both hard obstacles and softwireless signal strength fields;

FIG. 2 illustrates an example of a differential drive robot used byfirst responders in emergency situations;

FIG. 3 is a flowchart illustrating the workflow of an embodiment of acommunication-aware mobility process;

FIG. 4 illustrates an example of coupling between a guidance module anda robotics agent through velocity synchronization;

FIG. 5 illustrates an example of regions and variables used by aguidance module;

FIG. 6 is a flowchart illustrating components of an embodiment of aguidance module;

FIG. 7 illustrates safety sensitization of the guidance signal by makingthe magnitude of the tangential reference speed dependent on therelative location of the actual speed of the robot;

FIG. 8 illustrates a block diagram of an embodiment of a method used toconvert the safety-sensitized guidance signal into a control signal;

FIG. 9 illustrates a comparison of trajectories generated by: acommunication unaware method, communication-aware method, andsensor-based communication aware method;

FIG. 10 illustrates communication-aware, sensor-based trajectory alongwith the partial signal strength information used in generating thetrajectory;

FIG. 11 illustrates signal strength profile along the differenttrajectories of FIG. 9 along with their mean values;

FIG. 12 illustrates SNR shadowing caused by a small object;

FIG. 13 illustrates an example of communication-aware andcommunication-unaware trajectories in a highly cluttered environmentwith a single transmitter;

FIG. 14 illustrates the SNR profile along both paths of the example inFIG. 13;

FIG. 15 illustrates an example of transmitter tracking;

FIG. 16 illustrates an example of sensor-based transmitter tracking;

FIG. 17 illustrates an example of a 3D trajectory of an agent;

FIG. 18 illustrates an example of kinematic reference trajectory (blue)and actuated dynamic trajectory (red);

FIG. 19A illustrates a control signal, u1, corresponding to thetrajectory of the example in FIG. 17;

FIG. 19B illustrates a control signal, u2, corresponding to thetrajectory of the example in FIG. 17;

FIG. 19C illustrates a control signal, u3, corresponding to thetrajectory of the example in FIG. 17;

FIG. 19D illustrates a control signal, u4, corresponding to thetrajectory of the example in FIG. 17;

FIG. 19E illustrates a control signal, u5, corresponding to thetrajectory of the example in FIG. 17;

FIG. 19F illustrates a control signal, u6, corresponding to thetrajectory of the example in FIG. 17;

FIG. 20 illustrates a schematic diagram of an embodiment of a mobilerobot of the present disclosure; and

FIG. 21 illustrates an example of a schematic diagram of a dataprocessing system for performing navigation of the mobile robot.

FIG. 22 illustrates one implementation of a CPU shown in FIG. 21.

DETAILED DESCRIPTION

The present disclosure describes an integrated procedure and system forsteering a mobile robot 100 with nontrivial dynamics to a target zone inan unknown and unstructured environment while maintaining good wirelesscommunication channel characteristics. The procedure ensures that atarget position X_(T) can be reached along a well-behaved path. It alsoensures that hard obstacles (physical obstacles) and dead communicationzones can be avoided even when physical obstacles and communicationdead-zones are newly detected via onboard sensors 105, 106 while enroute to a designated target position X_(T). The procedure allows for asufficiently simple design that is readily compatible with VLSIimplementations and provides an actuation-friendly control signal thatreduces energy consumption and stress on a motion actuator 140 of themobile robot 100 being navigated. The procedure produces smooth,infinitely differentiable trajectories and generates motion that isintuitive and to a large extent predictable. The procedure keeps missionuncertainty under control.

The guidance technique disclosed herein is capable of generating anactuation signal U(X) for the motion actuator 140 that realizes theabove behavior for a wide class of robotics platforms described by thesystem equation (Equation 1),

$\begin{matrix}{{\frac{dX}{dt} = {T(\lambda)}}{\frac{d\; \lambda}{dt} = {F\left( {\lambda,U} \right)}}} & (1)\end{matrix}$

where X is the position vector of the robot and λ describes the localmotion variables such as the orientation of the platform and itstangential speed. The above model accommodates a differential drivemobile robot 100, such as that shown as an example in FIG. 2, which iscommonly used in first responder robotics. In other embodiments therobot may be a drone operating in three dimensions and/or not in directcontact with a ground surface. The following (Equation 2) shows theactuation of such a mobile robot 100,

$\begin{matrix}{\begin{bmatrix}\overset{.}{x} \\\overset{.}{y} \\\overset{.}{\theta} \\\overset{.}{v}\end{bmatrix} = \begin{bmatrix}{v \cdot {\cos (\theta)}} \\{v \cdot {\sin (\theta)}} \\u \\a\end{bmatrix}} & (2)\end{matrix}$

where x and y are the coordinates of the robot's location, θ and v arethe orientation and tangential speed of the robot respectively, u and aare the robot's control variables through which motion is actuated.

Exemplary embodiments of the present invention will be described belowwith reference to the drawings. In the drawings, the same elements aredenoted by the same reference numerals, and thus redundant descriptionsthereof are omitted as needed.

Exemplary Embodiment

Hereinafter, an exemplary embodiment of the present disclosure will begiven with reference to the drawings in terms of a mobile roboticsplatform (mobile robot 100). A workflow of components in an exampleprocedure for this embodiment is shown in FIG. 3. Mission data(including known topography or signal coverage, if available, and atarget location) is input to a guidance generation unit 110 of themobile robot 100. The guidance generation unit 110 converts the datainto a guidance vector field G(X) (hereinafter also referred to as a“guidance policy”) that marks, at each point in space, the directionalong which motion should proceed if the target is to be reached in anefficient, communication-aware manner. The vector that lies at thecurrent location of the mobile robot 100 is selected as the guidancevector.

The mobile robot 100 of this embodiment has a number of sensors 105, 106(see for example FIG. 20) onboard which are capable of detecting fieldinformation, for example, hard and soft obstacles. Hard obstacles γ maybe, for example, physical obstructions in a potential path to the targetposition X_(T), and soft obstacles σ may be, for example, areas to befavored or avoided based on high or low communication signal coverage,respectively. The sensors 105, 106 output detected field information tothe guidance generation unit 110.

Here, the operations of the guidance generation unit 110 will bedescribed in detail in accordance with the block diagram in FIG. 6.

The vector guidance policy G(X) is generated from an underlying scalarpotential field V(X) using the boundary value problem described in FIG.5 as an example. The perimeter of operation (H) is set so as to definethe workspace (field of movement) in which the mobile robot 100 shouldoperate.

If no information exists about physical obstacles (Γ) contained in theenvironment, then the hard obstacle description is initialized to theempty set Γ(0)=ϕ. Furthermore, if no information exists about signalstrength in the field of movement, i.e., soft obstacles (σ) contained inthe environment, then the signal strength is initialized to a smallpositive constant (σ(X,0)=ε).

In the case that field information about hard obstacles (Γs) is receivedfrom an obstacle detection sensor 105, the obstacle representation isadjusted such that Γ (X, t+dt)=Γ(X,t) ∪Γs).

Similarly, if field information about the signal strength field (σs) isreceived from a communication sensor 106, the region of the signalstrength field that contains the update (Ωs) is filled with the sensedfield (σ(X, t+dt)=σs(X) X ∈Ωs). The update should be performed such thatthe signal strength at the interface between the updated and existingregions is continuous.

The target location X_(T) is specified along with the start locationX_(S), and a small circular region (β(X)) of radius δ is created with Xsas its center where (β(X)={X:|X−Xs|=δ}).

Next, the boundary value problem (Equation 3) is solved.

∇·(σ·∇V)=0 X∈Π−Γ  (3)

where, V(X)=1 X∈β, V(X_(T))=0, ∂V(X)/∂n=0 X∈Γ

The start point Xo on β is selected such that that |∇V(Xo)| is thehighest. To move along a trajectory that would ensure that the target isreached while keeping good wireless channel characteristics, thereference velocity which motion has to proceed along is driven by thenormalized negative gradient field of V starting from the point Xo

$\begin{matrix}{{\overset{.}{X}{r(X)}} = {{G(X)} = {{{- \frac{\nabla{V(X)}}{{\nabla{V(X)}}}}{X(0)}} = {Xo}}}} & (4)\end{matrix}$

The generated guidance vector is passed to a conditioning stage (safetysensitization unit 120) that produces a safe guidance vector(hereinafter also referred to as a “safety sensitized policy”). Safetyis factored into the guidance signal based on the relative angle betweenthe actual speed (current speed) of the mobile robot 100 and theguidance vector. In the case that no new field information (i.e.,physical obstacles or change in communication signal strength) isdetected by the onboard sensors 105, 106 of the mobile robot 100, theguidance policy remains static and the safety sensitization simplyoutputs the guidance policy with no significant modification.

However, if new field information is detected by the onboard sensors105, 106, the guidance generation unit 110 appropriately updates theguidance policy G(X). This update to the guidance policy may likelycause a misalignment between the actual traveling speed (in accordancewith the previous guidance policy) and the newly generated guidancepolicy. The bigger this misalignment is, the bigger is the risk that therobot will collide with an obstacle or move into a region with poorcommunication characteristics. It is reasonable to order the robot toslowdown if the robot projects motion that is significantly differentfrom what is being told to project (even stop if it is going in theopposite direction). If there is a good alignment between motion and thecommands given, then the robot can proceed at full speed. This ideaenables the controller to effectively enforce compliance of the robot'smotion with the guidance signal hence enhancing mission safety in termsof collision and communication-outage avoidance.

Therefore, the safety sensitization unit 120 reduces the velocitymagnitude of the guidance policy such that a smooth and continuousreorientation of travel can be made and the mobile robot 100 does not,for example, collide with a newly detected obstacle or cross into acommunication dead zone due to a sudden change in the guidance policy.

The guidance policy is converted into an equivalent navigation controlsignal by treating the guidance vector as an imaginary referencevelocity (FIG. 4). The safety sensitization process aims to align theguidance vector with the velocity vector of the mobile robot 100 andallows for opportunistically exploiting information with minimaldisruption to existing plan of action. This ensures the conversion ofthe guidance vector into a control signal when full information isavailable and the guidance field is not changing with time. The safetyconditioning makes it possible to do such a conversion when the guidancefield is evolving under the influence of sensory feedback.

Here, the operations of the safety sensitization unit of this embodimentwill be described in detail.

When full information is available and the guidance policy is static,the mobile robot 100 exactly traverses the guidance trajectory if theinitial velocity of the mobile robot 100 and the initial gradientguidance field are in phase. It is possible to still ensure thecompliance of the mobile robot 100 with the guidance policy withouthaving to stop and re-orient itself each time a sensory update isreceived. This is carried-out by modulating the magnitude of theguidance field with a positive factor (see FIG. 7) of a maximum value 1and minimum value b. This factor basically reduces the velocitymagnitude of the robot proportional to the error in alignment. Thus,gradually as the robot realigns with the gradient guidance field, thefactor starts approaching 1. If the velocity magnitude is not modulated,the error in alignment increases especially for paths that have sharpturns.

The following normalized dot and cross products are constructed by thesafety sensitization unit 120 using the guidance policy output by theguidance generation unit 110 and the actual speed (current motionvector).

$\begin{matrix}{{{DP} = \frac{\left( {\overset{.}{X}(X)} \right) \circ \left( {- {\nabla{V(X)}}} \right)}{{{\overset{.}{X}(X)}}{{\nabla{V(X)}}}}},{{CP} = \frac{\left( {\overset{.}{X}(X)} \right) \times \left( {- {\nabla{V(X)}}} \right)}{{{\overset{.}{X}(X)}}{{\nabla{V(X)}}}}}} & (5)\end{matrix}$

A variable η is constructed in accordance with:

$\begin{matrix}{\eta = \left\lbrack \begin{matrix}{CP} & {{{if}\mspace{14mu} {DP}} > 0} \\{{sign}({CP})} & {{{if}\mspace{14mu} {DP}} \leq 0}\end{matrix} \right.} & (6)\end{matrix}$

A scaling factor c is constructed in accordance with:

c=(1−b)·(1−|η|)+b  (7)

The resulting scaled guidance signal Q(X) which is output to the motionactuation unit 130 as the safety sensitized policy is:

$\begin{matrix}{{Q(X)} = {{- c} \cdot \frac{\nabla V}{{\nabla V}}}} & (8)\end{matrix}$

Next, the operations of the motion actuation unit 130 of the presentembodiment will be described in accordance with the example blockdiagram shown in FIG. 8. The conversion of the communication awareguidance signal into an equivalent actuation signal can instruct themobile robot's actuators of motion to project an action that is inconformity with guidance.

The following procedure may be calculated in the motion actuation unit130 and used for the conversion. First, the difference between thesafety-sensitized guidance signal and the actual tangential speed of theagent is calculated and scaled with a tunable positive constant K1 whichgives a first error signal E1.

E1=K1·(Q(X)−{dot over (X)}  (9)

Next, this error in the workspace domain is converted to a guidancesignal in the configuration space domain using the Jacobian matrixcomputed as F1.

$\begin{matrix}{{F\; 1} = \frac{\partial{T(\lambda)}}{\partial\lambda}} & (10)\end{matrix}$

Thereafter, the error in configuration space E2 is obtained using thetransformed error as the ‘guidance’ signal in configuration space. Theerror in local coordinates is multiplied by another tunable positiveconstant K2.

E2=K2·(F1^(T) ·E1−{dot over (λ)})  (11)

The Jacobian matrix, given below, then transforms the error in theconfiguration space guidance to the derivative of the control signal asF2.

$\begin{matrix}{{F\; 2} = \frac{\partial{F\left( {\lambda,U} \right)}}{\partial U}} & (12)\end{matrix}$

The derivative of the actuation signal is then computed as:

{dot over (U)}=F2^(T) ·E2  (13)

The actuation signal is computed by integrating its derivative

$\begin{matrix}{{U(t)} = {\int_{0}^{t}{\overset{.}{U} \cdot {dt}}}} & (14)\end{matrix}$

The control signal U(X) is then fed to the mobile robot 100 in order toactuate motion that results in the robot moving along the gradient ofthe potential field obtained as part of the guidance stage, and thesensory data collected by the sensors 105, 106 are fed to the guidancegeneration unit 110 for processing. When the mobile robot 100 reachesthe target position X_(T), the mobile robot 100 stops, at which time anew target position X_(T) may be assigned as necessary.

The above exemplary embodiment is described in terms functional unitsimplemented in hardware included in a mobile robotics platform. Thesefunctional hardware units may be implemented in such a way as to beindividual from one another or integrated with one another, sharing likecomponents such as logic processing and memory storage resources, asnecessary, and is not particularly limited as long as the functionalhardware units are able to perform the functions as taught in thisdisclosure. It should also be clear to persons of skill in the art thatthe procedures performed by the functional units may also be performedin the steps of a method or as software instructions implementingequivalent functions of the hardware units to achieve the advantageouseffects of the present disclosure.

Experimental Results

This section provides basic results that demonstrate basic capabilitiesof the present procedure. FIG. 9 shows three trajectories connecting astarting point to a target in free space that contains one transmitter.Three trajectories were generated to the target. The first trajectory(blue line) was generated in a communication unaware manner by settingthe communication signal strength field σ to a constant value. The othertwo were generated using the communication-aware method disclosedherein. The red trajectory was generated using full information aboutthe signal strength field and the other using partial informationcontained in a 5-meter radius (FIG. 10). As can be seen, thecommunication aware trajectories favored the high signal-to-noise ratio(SNR) regions with modest increase in the paths' lengths. FIG. 11 showsthe SNR profile along each of these trajectories.

The advantages of the present technique become salient when theenvironment contains clutter. Clutter causes many artifacts that aredetrimental to the signal strength field which could even cause outage(RF shadows) in some parts of the environment. FIG. 12 shows anenvironment that contains a transmitter and a small object. The objectis causing an RF shadow region of low SNR values to appear. Thecommunication aware trajectory generation method is used with fullinformation about the SNR field to generate a path from a start point toa target point. As can be seen, the method abandons the direct shortestpath that passes through the low SNR region and instead generates a pathwith sufficient length that remains inside the high SNR region.

The same behavior of the method is observed even when the clutterbecomes more geometrically complicated. FIG. 13 shows a clutteredenvironment with one transmitter. It also shows the communicationunaware path (blue line) and the communication aware path (red line).While both paths avoided collision with obstacles, the communicationunaware path passed through communication dead-zones. The communicationaware trajectory exhibited a modest increase in the path length andremained in the high SNR region. FIG. 14 shows the SNR profile alongeach path and a gain in average signal strength of about 35 dB.

The example in FIG. 15 demonstrates the ability of the method to locatetransmitters. The figure shows two paths, one uses full informationabout the signal strength field and the other uses only sensor-basedinformation in a 5-meter radius (FIG. 16). Both paths were able toaccurately locate the transmitter with almost identical performance.

This example demonstrates the ability of the suggested method not onlyto generate a communication-aware reference trajectory but to alsogenerate the actuation signal that can correctly actuatecommunication-aware motion in an agent. A three-dimensional agent (14)with complex nonlinear dynamics and redundant actuation (u1, . . . , u6)is used to demonstrate this feature.

{dot over (x)}=v·CφCθ

{dot over (y)}=v·SφSθ

ż=v·Cθ

{dot over (v)}=u ₁ ·u ₄

{dot over (θ)}=cos(u ₂)+u ₃ ² +u ₅

{dot over (φ)}=cos(u ₂)sin(u ₄)+u ₆  (14)

The agent is required to synthesize the control signal that moves itfrom a start point to a target point while increasing its elevation fromzero to two along the z-axis. The agent must maintain a good positionduring the execution of the task. The actuated 3D trajectory is shown inFIG. 17. The projection of both the reference trajectory (blue) andactuated trajectory (red) on the X-Y plane are superimposed on theutility map. As can be seen the actuated path is almost identical to thereference path. Both of them remain effectively confined to the regionwith high utility value. The control signals generating this trajectoryare shown in FIGS. 19A-19F for control signals u1-u6 respectively. Ascan be seen, they are all bounded and well-behaved. The signals u₁-u₆shown in FIGS. 19A-19F are control signals for a fixed wing UAV given bythe following dynamic model. Where x, y and z are its spatialcoordinates, v is its linear velocity and θ & φ represent theorientation of the UAV in 3-D space (see Eq. 14 above).

It should be apparent from the foregoing that numerous modifications andvariations of the present disclosure are possible in light of the aboveteachings. It is therefore to be understood that within the scope of theappended claims, the invention may be practiced otherwise than asspecifically described herein.

For example, the mobile robot 100 of the exemplary embodiment is adifferential drive robot; however, the techniques for navigating themobile robot 100 disclosed herein could appropriately be applied to, forexample, an aquatic or aerial drone. The guidance field may be convertedto a control field suitable for practical robotics platforms, and theactuation signal may be appropriately modified to accommodate any typeof robotics platform as well.

Further, in the description of the operation of the mobile robot 100, atarget position X_(T) is selected and the mobile robot 100 continues tothe target location until the target location is reached. However, it isalso possible for a remote operator to change the target location whilethe mobile robot 100 is en route before the target location is reached.In such a situation, similar to when new field information is receivedby the mobile robot's sensors, the guidance policy would necessarily beupdated which may cause a need for safety sensitization of the guidancepolicy. Therefore, safety sensitization of the guidance policy is usefulfor any situation in which the guidance policy and the actual travelingvector may become misaligned.

In addition, the disclosed operations are compatible with allowing aremote user to assume full control of motion, influence the motion, ortotally leave the decision on motion to the mobile robot 100 duringoperation. Such features may be included, as necessary, according todesign requirements.

A global positioning system (GPS) sensor may be implemented into therobotics platform but is not required for the operations disclosedherein. Even in the absence of a global coordinate system, the mobilerobot 100 can efficiently function in a local, self-referentialcoordinate system and can instruct a user how to locate itself in space,for example, to improve wireless reception. Also, the mobile robot canbe used to approximately locate wireless transmission sources usinglocal sensing of signal strength.

Both slow and fast fading may be accommodated in the steering process,and in the case of fast fading, it is possible to transmit servo-gradesignals over wireless channels, if necessary.

In addition, the disclosed procedure allows an agent to move to a targetlocated amidst clutter along a short path that has good wirelessreception characteristics when no information about the field ofmovement is available in advance and the agent is obtaining spatial andwireless signal strength information locally; however, information aboutthe field of movement may be provided in advance, further improving theefficiency of guidance even if the field information is partial orinaccurate. In the case of partial or inaccurate field information,improvement of performance is close in quality to that when informationis fully available.

The exemplary embodiment above utilizes both an obstacle detectionsensor and a communication sensor, but may also operate with merely oneor the other, for example, only accommodating spatial information andignoring signal strength information.

The exemplary circuit elements described in the context of the presentdisclosure may be replaced with other elements and structureddifferently than the examples provided herein. Moreover, circuitryconfigured to perform features described herein may be implemented inmultiple circuit units (e.g., chips), or the features may be combined incircuitry on a single chipset, as shown on FIG. 21.

FIG. 21 shows a schematic diagram of a data processing system, accordingto certain embodiments, for performing navigation of the mobile robot.The data processing system is an example of a computer in which code orinstructions implementing the processes of the illustrative embodimentsmay be located.

In FIG. 21, data processing system 200 employs a hub architectureincluding a north bridge and memory controller hub (NB/MCH) 225 and asouth bridge and input/output (I/O) controller hub (SB/ICH) 220. Thecentral processing unit (CPU) 230 is connected to NB/MCH 225. The NB/MCH225 also connects to the memory 245 via a memory bus, and connects tothe graphics processor 250 via an accelerated graphics port (AGP). TheNB/MCH 225 also connects to the SB/ICH 220 via an internal bus (e.g., aunified media interface or a direct media interface). The CPU Processingunit 230 may contain one or more processors and even may be implementedusing one or more heterogeneous processor systems.

For example, FIG. 22 shows one implementation of CPU 230. In oneimplementation, the instruction register 338 retrieves instructions fromthe fast memory 340. At least part of these instructions are fetchedfrom the instruction register 338 by the control logic 336 andinterpreted according to the instruction set architecture of the CPU230. Part of the instructions can also be directed to the register 332.In one implementation the instructions are decoded according to ahardwired method, and in another implementation the instructions aredecoded according a microprogram that translates instructions into setsof CPU configuration signals that are applied sequentially over multipleclock pulses. After fetching and decoding the instructions, theinstructions are executed using the arithmetic logic unit (ALU) 334 thatloads values from the register 332 and performs logical and mathematicaloperations on the loaded values according to the instructions. Theresults from these operations can be feedback into the register and/orstored in the fast memory 340. According to certain implementations, theinstruction set architecture of the CPU 230 can use a reducedinstruction set architecture, a complex instruction set architecture, avector processor architecture, a very large instruction wordarchitecture. Furthermore, the CPU 230 can be based on the Von Neumanmodel or the Harvard model. The CPU 230 can be a digital signalprocessor, an FPGA, an ASIC, a PLA, a PLD, or a CPLD. Further, the CPU230 can be an x86 processor by Intel or by AMD; an ARM processor, aPower architecture processor by, e.g., IBM; a SPARC architectureprocessor by Sun Microsystems or by Oracle; or other known CPUarchitecture.

Referring again to FIG. 21, the data processing system 200 can includethat the SB/ICH 220 is coupled through a system bus to an I/O Bus, aread only memory (ROM) 256, universal serial bus (USB) port 264, a flashbinary input/output system (BIOS) 268, and a graphics controller 258.PCI/PCIe devices can also be coupled to SB/ICH 220 through a PCI bus262.

The PCI devices may include, for example, Ethernet adapters, add-incards, and PC cards for notebook computers. The hard disk drive 260 andCD-ROM 266 can use, for example, an integrated drive electronics (IDE)or serial advanced technology attachment (SATA) interface. In oneimplementation the I/O bus can include a super I/O (SIO) device.

Further, the hard disk drive (HDD) 260 and optical drive 266 can also becoupled to the SB/ICH Y20 through a system bus. In one implementation, akeyboard 270, a mouse 272, a parallel port 278, and a serial port 276can be connected to the system bust through the I/O bus. Otherperipherals and devices that can be connected to the SB/ICH 220 using amass storage controller such as SATA or PATA, an Ethernet port, an ISAbus, a LPC bridge, SMBus, a DMA controller, and an Audio Codec.

Moreover, the present disclosure is not limited to the specific circuitelements described herein, nor is the present disclosure limited to thespecific sizing and classification of these elements. For example, theskilled artisan will appreciate that the circuitry described herein maybe adapted based on changes on battery sizing and chemistry, or based onthe requirements of the intended back-up load to be powered.

Thus, the foregoing discussion discloses and describes merely exemplaryembodiments of the present invention. As will be understood by thoseskilled in the art, the present invention may be embodied in otherspecific forms without departing from the spirit or essentialcharacteristics thereof. Accordingly, the disclosure of the presentinvention is intended to be illustrative, but not limiting of the scopeof the invention, as well as other claims. The disclosure, including anyreadily discernible variants of the teachings herein, defines, in part,the scope of the foregoing claim terminology such that no inventivesubject matter is dedicated to the public.

REFERENCE SIGNS

-   100 Mobile Robot-   105 Obstacle Detection Sensor-   106 Communication Sensor-   110 Guidance Generation Unit-   120 Safety Sensitization Unit-   130 Motion Actuation Unit-   140 Motion Actuator-   200 Data Processing System-   220 Southbridge/ICH-   225 Northbridge/MCH-   230 CPU-   245 Memory-   250 Graphics Processor-   256 ROM-   258 Graphics Controller-   260 Hard Disk Drive-   262 PCI-   264 USB-   266 Optical Drive-   270 Keyboard-   272 Mouse-   276 Serial Port-   278 Parallel Port-   332 Register-   334 ALU-   336 Control Logic-   338 Instruction Register-   340 Fast Memory

1. A mobile robot comprising: a motion actuator; at least one detection sensor configured to detect field information in a movement field of the mobile robot; a guidance generation unit configured to generate a motion guidance policy to a target position from a current position, the motion guidance policy being updated by the guidance generation unit when the field information has been received from the at least one detection sensor; a safety sensitization unit configured to generate a safety sensitized policy which is the motion guidance policy with a reduced velocity magnitude relative to an angle between the motion guidance policy and the current motion of the mobile robot; and a motion actuation unit configured to determine an actuation signal for instructing the motion actuator to project the current motion of the mobile robot in conformity with the safety sensitized policy provided by the safety sensitization unit.
 2. The mobile robot of claim 1, wherein the safety sensitization unit generates the safety sensitized policy by modulating the magnitude of the guidance policy using a positive factor of 1 to b, where b is less than
 1. 3. The mobile robot of claim 1, wherein the at least one detection sensor includes an obstacle detection sensor configured to detect physical obstacles within the movement field of the mobile robot and outputs information about the physical obstacles as at least part of the field information.
 4. The mobile robot of claim 1, wherein the at least one detection sensor includes a communication sensor configured to detect a signal coverage of a wireless communication signal and outputs information about the signal coverage as at least part of the field information.
 5. The mobile robot of claim 1, wherein the at least one detection sensor includes: an obstacle detection sensor configured to detect physical obstacles within the movement field of the mobile robot and outputs information about the physical obstacles as at least part of the field information, and a communication sensor configured to detect a signal coverage of a wireless communication signal and outputs information about the signal coverage as at least part of the field information.
 6. The mobile robot of claim 3, wherein the guidance generation unit updates the motion guidance policy such that movement into the physical obstacles is avoided.
 7. The mobile robot of claim 4, wherein the guidance generation unit updates the motion guidance policy such that movement into areas with low signal coverage is avoided and movement into areas with high signal coverage is favored.
 8. The mobile robot of claim 1, wherein the motion guidance policy is generated in-part using field information provided to the guidance generation unit in advance.
 9. The mobile robot of claim 1, wherein the motion actuator is a plurality of actuators configured to perform differential driving of the mobile robot.
 10. The mobile robot of claim 1, wherein the at least one detection sensor includes a GPS sensor.
 11. A method of navigating a mobile robot, comprising the steps of: detecting field information in a movement field of the mobile robot; generating a movement guidance policy to a target position from a current position; updating, when field information is detected in the detecting step, the motion guidance policy based on the detected field information; generating a safety sensitized policy by reducing a velocity magnitude of the movement guidance policy relative to an angle between the motion guidance policy and a current motion of the mobile robot; generating an actuation signal for actuating the motion of the mobile robot in conformity with the safety sensitized policy; and driving the mobile robot in accordance with the actuation signal.
 12. The method of claim 11, wherein the safety sensitized policy is generated by modulating the magnitude of the guidance policy using a positive factor of 1 to b, where b is less than
 1. 13. The method of claim 11, wherein the field information detected in the detecting step is, at least in part, information about physical obstacles within the movement field of the mobile robot.
 14. The method of claim 11, wherein the field information detected in the detecting step is, at least in part, information about a signal coverage of a wireless communication signal within the movement field of the mobile robot.
 15. The method of claim 11, wherein the field information detected in the detecting step is, at least in part, information about physical obstacles within the movement field of the mobile robot and information about a signal coverage of a wireless communication signal within the movement field of the mobile robot.
 16. The method of claim 13, wherein the motion guidance policy is updated, in the updating step, such that movement into the physical obstacles is avoided.
 17. The method of claim 14, wherein the motion guidance policy is updated, in the updating step, such that movement into areas with low signal coverage is avoided and movement into areas with high signal coverage is favored.
 18. The method of claim 10, wherein the motion guidance policy is generated in-part using field information provided in advance.
 19. The method of claim 10, wherein the actuation signal for actuating the motion of the mobile robot is a plurality of signals for differentially driving the mobile robot.
 20. A non-transitory computer-readable storage medium storing instructions to cause a computer to perform the steps of: detecting field information in a movement field of a mobile robot; generating a movement guidance policy to a target position from a current position; updating, when field information is detected in the detecting step, the motion guidance policy based on the detected field information; generating a safety sensitized policy by reducing a velocity magnitude of the movement guidance policy relative to an angle between the motion guidance policy and a current motion of the mobile robot; generating an actuation signal for actuating the motion of the mobile robot in conformity with the safety sensitized policy; and driving the mobile robot in accordance with the actuation signal. 